Seismic Inference using Genetic Algorithms

A flood of reliable seismic data will soon arrive. The migration to largertelescopes on the ground may free up 4-m class instruments for multi-sitecampaigns, and several forthcoming satellite missions promise to yieldnearly uninterrupted long-term coverage of many pulsating stars. We willthen face the challenge of determining the fundamental properties of thesestars from the data, by trying to match them with the output of ourcomputer models. The traditional approach to this task is to make informedguesses for each of the model parameters, and then adjust them iterativelyuntil an adequate match is found. The trouble is: how do we know that oursolution is unique, or that some other combination of parameters will notdo even better? Computers are now sufficiently powerful and inexpensivethat we can produce large grids of models and simply compare all ofthem to the observations. The question then becomes: what range ofparameters do we want to consider, and how many models do we want tocalculate? This can minimize the subjective nature of the process, but itmay not be the most efficient approach and it may give us a false sense ofsecurity that the final result is correct, when it is really justoptimal. I discuss these issues in the context of recent advances inthe asteroseismological analysis of white dwarf stars.     

CCD photometry inVRI bands of the galactic cluster NGC 2818

bdAbstract The open cluster NGC 2818 containing a planetary nebula has been observed inVRI bands using the CCD system at prime focus of the 2.3-metre Vainu Bappu Telescope. The study extending to starsV ∼ 21 magnitude establishes the distance modulus as(m-M) ₀ = 12.9 ±0.1 for the cluster. Based on the fitting of theoretical isochrones computed for solar metallicity, an age of 5(±1) × 10₈ years has been assigned to the cluster. Association of the planetary nebula with the cluster indicates that the progenitor mass of the planetary nebula on the main sequence is ≥2.5M_⊙ Based on observations obtained with the Vainu Bappu Telescope.     

The evolution of binary fractions in globular clusters

We study the evolution of binary stars in globular clusters using a new Monte Carlo approach combining a population synthesis code ( startrack ) and a simple treatment of dynamical interactions in the dense cluster core using a new tool for computing three- and four-body interactions ( fewbody ). We find that the combination of stellar evolution and dynamical interactions (binary–single and binary–binary) leads to a rapid depletion of the binary population in the cluster core. The maximum binary fraction today in the core of a typical dense cluster such as 47 Tuc, assuming an initial binary fraction of 100 per cent, is only ∼ 5–10 per cent. We show that this is in good agreement with recent Hubble Space Telescope observations of close binaries in the core of 47 Tuc, provided that a realistic distribution of binary periods is used to interpret the results. Our findings also have important consequences for the dynamical modelling of globular clusters, suggesting that 'realistic models' should incorporate much larger initial binary fractions than has usually been the case in the past.